class_docstr: Most tests done in the base class LinearOperatorDerivedClassTest.
code: def test_solve_adjoint_operator(self):
      matrix1 = self.evaluate(
          linear_operator_test_util.random_tril_matrix(
              [4, 4], dtype=dtypes.float64, force_well_conditioned=True
          )
      )
      matrix2 = np.random.randn(4, 4)
      full_matrix1 = linalg.LinearOperatorLowerTriangular(
          matrix1, is_non_singular=True
      )
      full_matrix2 = linalg.LinearOperatorFullMatrix(matrix2)
  
      self.assertAllClose(
          self.evaluate(linalg.triangular_solve(matrix1, matrix2.T)),
          self.evaluate(
              full_matrix1.solve(
                  full_matrix2, adjoint_arg=True
              ).to_dense()
          ),
      )
  
      self.assertAllClose(
          self.evaluate(
              linalg.triangular_solve(matrix1.T, matrix2, lower=False)
          ),
          self.evaluate(
              full_matrix1.solve(full_matrix2, adjoint=True).to_dense()
          ),
      )
  
      self.assertAllClose(
          self.evaluate(
              linalg.triangular_solve(matrix1.T, matrix2.T, lower=False)
          ),
          self.evaluate(
              full_matrix1.solve(
                  full_matrix2, adjoint=True, adjoint_arg=True
              ).to_dense()
          ),
      )
  
imports: import numpy
  from tensorflow.python.framework import config
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.ops.linalg import linalg
  from tensorflow.python.ops.linalg import linear_operator_adjoint
  from tensorflow.python.ops.linalg import linear_operator_test_util
  from tensorflow.python.platform import test
label_desc: Use image node_id 12 for calling the LinearOperatorAdjointTest obj's underlying member method code with example usage: obj.test_solve_adjoint_operator() without return types